rThomas

0th

Percentile

Simulate Thomas Process

Generate a random point pattern using the Thomas cluster process.

Keywords
spatial
Usage
rThomas(lambda, sigma, mu, win = owin(c(0,1),c(0,1)))
Arguments
lambda
Intensity of the Poisson process of cluster centres. A single positive number.
sigma
Standard deviation of displacement of a point from its cluster centre.
mu
Expected number of points per cluster.
win
Window in which to simulate the pattern. An object of class "owin" or something acceptable to as.owin.
Details

This algorithm generates a realisation of the Thomas process, a special case of the Neyman-Scott process. The algorithm generates a uniform Poisson point process of ``parent'' points with intensity lambda. Then each parent point is replaced by a random cluster of points, the number of points per cluster being Poisson (mu) distributed, and their positions being isotropic Gaussian displacements from the cluster parent location.

Value

  • The simulated point pattern (an object of class "ppp").

See Also

rpoispp, rNeymanScott

Aliases
  • rThomas
Examples
library(spatstat)
  X <- rThomas(10, 0.2, 5)
Documentation reproduced from package spatstat, version 1.0-1, License: GPL version 2 or newer

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